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Model-based scenario analyses of future energy systems often come to deviating results and conclusions when different models are used. This may be caused by heterogeneous input data and by inherent differences in model formulations. The representation of technologies for the conversion, storage, use, and transport of energy is usually stylized in comprehensive system models in order to limit the size of the mathematical problem, and may substantially differ between models. This paper presents a systematic comparison of nine power sector models with sector coupling. We analyze the impact of differences in the representation of technologies, optimization approaches, and further model features on model outcomes. The comparison uses fully harmonized input data and highly simplified system configurations to isolate and quantify model-specific effects. We identify structural differences in terms of the optimization approach between the models. Furthermore, we find substantial differences in technology modeling primarily for battery electric vehicles, reservoir hydro power, power transmission, and demand response. These depend largely on the specific focus of the models. In model analyses where these technologies are a relevant factor, it is therefore important to be aware of potential effects of the chosen modeling approach. For the detailed analysis of the effect of individual differences in technology modeling and model features, the chosen approach of highly simplified test cases is suitable, as it allows to isolate the effects of model-specific differences on results. However, it strongly limits the model's degrees of freedom, which reduces its suitability for the evaluation of fundamentally different modeling approaches.
In order to ensure security of supply in a future energy system with a high share of volatile electricity generation, flexibility technologies are needed. Industrial demand-side management ranks as one of the most efficient flexibility options. This paper analyses the effect of the integration of industrial demand-side management through the flexibilisation of aluminium electrolysis and other flexibilities of the electricity system and adjacent sectors. The additional flexibility options include electricity storage, heat storage in district heating networks, controlled charging of electric vehicles, and buffer storage in hydrogen electrolysis. The utilisation of the flexibilities is modelled in different settings with an increasing share of renewable energies, applying a dispatch model. This paper compares which contributions the different flexibilities can make to emission reduction, avoidance of curtailment, and reduction of fuel and CO2 costs, and which circumstances contribute to a decrease or increase of overall emissions with additional flexibilities. The analysis stresses the rising importance of flexibilities in an energy system based on increasing shares of renewable electricity generation, and shows that flexibilities are generally suited to reduce carbon emissions. It is presented that the relative contribution towards the reduction of curtailment and costs of flexibilisation of aluminium electrolysis are high, whereby the absolute effect is small compared to the other options due to the limited number of available processes.
In recent years, most countries in the Middle East and North Africa (MENA), including Jordan, Morocco and Tunisia, have rolled out national policies with the goal of decarbonising their economies. Energy policy goals in these countries have been characterised by expanding the deployment of renewable energy technologies in the electricity mix in the medium term (i.e., until 2030). This tacitly signals a transformation of socio-technical systems by 2030 and beyond. Nevertheless, how these policy objectives actually translate into future scenarios that can also take into account a long-term perspective up to 2050 and correspond to local preferences remains largely understudied. This paper aims to fill this gap by identifying the most widely preferred long-term electricity scenarios for Jordan, Morocco and Tunisia. During a series of two-day workshops (one in each country), the research team, along with local stakeholders, adopted a participatory approach to develop multiple 2050 electricity scenarios, which enabled electricity pathways to be modelled using Renewable Energy Pathway Simulation System GIS (renpassG!S). We subsequently used the Analytical Hierarchy Process (AHP) within a Multi-Criteria Analysis (MCA) to capture local preferences. The empirical findings show that local stakeholders in all three countries preferred electricity scenarios mainly or even exclusively based on renewables. The findings demonstrate a clear preference for renewable energies and show that useful insights can be generated using participatory approaches to energy planning.
Distributed cogeneration units are flexible and suited to providing balancing power, thereby contributing to the integration of renewable electricity. Against this background, we analysed the technical potential and ecological impact of CHP (combined heat and power) systems on the German minutes reserve market for 2010, 2020 and 2030. Typical CHP plants (from 1 to 2800 kWel) were evaluated in relation to typical buildings or supply cases in different sectors. The minutes reserve potential was determined by an optimisation model with a temporal resolution of 15 min. The results were scaled up to national level using a scenario analysis for the future development of CHP. Additionally, the extent to which three different flexibility measures (double plant size/fourfold storage volume/emergency cooler) increase the potential provision of balancing power was examined. Key findings demonstrate that distributed CHP could contribute significantly to the provision of minutes reserve in future decades. Flexibility options would further enhance the theoretical potential. The grid-orientated operating mode slightly increases CO2 emissions compared to the heat-orientated mode, but it is still preferable to the separate generation of heat and power. However, the impacts of a flexible mode depend greatly on the application and power-to-heat ratio of the individual CHP system.